System and method for optimizing camera settings

ABSTRACT

There is provided an electronic system including an image capturing device and a comparator coupled to the image capturing device. The image capturing device is operable for capturing a live image. The comparator generates a feedback signal by comparing the live image with a reference image and adjusts at least one setting of the image capturing device by the feedback signal.

TECHNICAL FIELD

The invention relates to the field of cameras.

BACKGROUND

A facial recognition system is a system that can automatically identifya person by matching a live image of the person to a reference image.

FIG. 1 illustrates a conventional facial recognition system 100including a camera 102, a reference image database 104, and a comparator106. Some reference images are stored in the reference image database104. The camera 102 captures a live image of a user and forwards thelive image to the comparator 106. The comparator 106 compares the liveimage with the reference images in the reference image database 104, andgenerates a recognition result indicating whether the live image canmatch to a reference image.

This conventional facial recognition system may perform well when thecurrent environment (the lighting and direction of lighting, etc.) issimilar to the environment in which the reference image is taken.However, when the current environment is different from the environmentin which the reference image is taken, the performance of the facialrecognition system can drop significantly and the live image of the usermay not match to any reference image in the database, which may lead toa high possibility of recognition failure.

SUMMARY

According to one embodiment of the invention, there is provided anelectronic system including an image capturing device and a comparatorcoupled to the image capturing device. The image capturing device isoperable for capturing a live image. The comparator generates a feedbacksignal by comparing the live image with a reference image and adjusts atleast one setting of the image capturing device by the feedback signal.

BRIEF DESCRIPTION OF THE DRAWINGS

Features and advantages of embodiments of the invention will becomeapparent as the following detailed description proceeds, and uponreference to the drawings, where like numerals depict like elements, andin which:

FIG. 1 illustrates a conventional facial recognition system.

FIG. 2 illustrates a facial recognition system, in accordance with oneembodiment of the present invention.

FIG. 3 illustrates a computer system, in accordance with one embodimentof the present invention.

FIG. 4 illustrates a flowchart of optimizing camera settings, inaccordance with one embodiment of the present invention.

DETAILED DESCRIPTION

Reference will now be made in detail to the embodiments of the presentinvention. While the invention will be described in conjunction withthese embodiments, it will be understood that they are not intended tolimit the invention to these embodiments. Additional advantages andaspects of the present disclosure will become readily apparent to thoseskilled in the art from the following detailed description. As will bedescribed, the present disclosure is capable of modification in variousobvious respects, all without departing from the spirit of the presentdisclosure. Accordingly, the drawings and description are to be regardedas illustrative in nature, and not as limitative.

FIG. 2 illustrates a facial recognition system 200, in accordance withone embodiment of the present invention. The facial recognition system200 includes an image capturing device, such as a camera 202, areference image database 204, and a comparator 206. One or morereference images can be stored in the reference image database 204. Thecamera 202 is capable of capturing a live image. The comparator 206 iscoupled to the camera 202 and is capable of generating a feedback signalto the camera 202 by comparing the live image with at least onereference image and is capable of adjusting at least one setting of thecamera 202 based on the feedback signal. The comparator 206 is furthercapable of determining a direction of adjustment of the camerasetting(s).

In operation, the camera 202 captures a first live image of a person(e.g., a user of the facial recognition system 200) and forwards thefirst live image to the comparator 206. The comparator 206 compares thefirst live image with the reference image(s) in the reference imagedatabase 104 to determine a first matching percentage which can indicatea similarity between the first live image and the reference image(s),and to determine whether the first live image is matched to a referenceimage of a person (or matched to a group of reference images of aperson), in one embodiment.

In one embodiment, the reference image database 204 stores multiplereference images of multiple persons, and each person has acorresponding reference image. The first matching percentage can be apercentage that the first live image matches to a reference image of aperson, which has the highest similarity to the first live image. Forexample, assume that the reference image database 104 stores threereference images representing three persons A, B and C respectively. Thesimilarity between the first live image and the reference image ofperson B is higher than the similarity between the first live image andthe reference image of person A, and is also higher than the similaritybetween the first live image and the reference image of person C. Assuch, the first matching percentage is a percentage that the first liveimage matches to the reference image of person B, which indicates asimilarity between the first live image and the reference image ofperson B, in one embodiment.

In another embodiment, the reference image database 204 stores multiplereference images of multiple persons, and each person has a group ofcorresponding reference images. The first matching percentage can be apercentage that the first live image matches to a group of referenceimages of a person, which have the highest similarity to the first liveimage. For example, assume that the reference image database 104 storesthree group of reference images representing three persons A, B and Crespectively. The similarity between the first live image and the groupof reference images of person B is higher than the similarity betweenthe first live image and the group of reference images of person A, andis also higher than the similarity between the first live image and thegroup of reference images of person C. As such, the first matchingpercentage is a percentage that the first live image matches to thegroup of reference images of person B, which indicates a similaritybetween the first live image and the group of reference images of personB, in one embodiment.

Furthermore, the comparator 206 can generate a feedback signal accordingto a result of the comparison. For example, the comparator 206 cangenerate a feedback signal to adjust one or more camera settings if nomatched reference image is found (e.g., the first matching percentage isless than a predetermined threshold). Advantageously, at least onesetting (e.g., an image brightness setting, an image contrast setting,an image color setting, a zoom-in/zoom-out setting, etc.) of the camera202 can be adjusted by the feedback signal to obtain a better camerasetting to capture a second live image. More specifically, the feedbacksignal can adjust one or more camera settings to reproduce the originallighting and/or color conditions of the reference image(s), in oneembodiment. As such, a matching percentage of the second live imagebased on the adjusted camera setting(s) can be increased, and thusincreasing the possibility of a successful recognition.

In one embodiment, the comparator 206 generates a feedback signal toadjust a first setting, such as an image brightness setting, e.g., toincrease the image brightness. The feedback signal can include somecommands that can adjust the camera settings through a driver of thecamera, in one embodiment.

The camera 202 captures a second live image based on the adjustedsetting and forwards the second live image to the comparator 206. Thecomparator 206 compares the second live image with the referenceimage(s) to determine a second matching percentage which can indicate asimilarity between the second live image and the reference image(s), inone embodiment. The second matching percentage can be determined in away that is similar to the way in determining the first matchingpercentage described above and will not be repetitively described hereinfor purposes of brevity and clarity.

In one embodiment, if the second matching percentage is greater than thefirst matching percentage, the comparator 206 can generate a feedbacksignal to further adjust the first setting in the same direction, e.g.,to further increase the image brightness, so as to capture a third liveimage which can be brighter than the second live image, and make thecomparison again. In one embodiment, if the second matching percentageis less than the first matching percentage, the comparator 206 generatesa feedback signal to adjust the first setting in an opposite direction,e.g., to decrease the image brightness, so as to capture a third liveimage which can be darker than the second live image. Advantageously, byrepeating the aforementioned process, e.g., adjusting the first settingrepetitively according to the feedback signal, the first setting can beautomatically optimized so as to reproduce the original condition (e.g.,lighting condition) of the reference image(s).

After adjusting the first setting (e.g., the image brightness setting inthe above example) repetitively, the system can further adjust othercamera settings, e.g., a second setting, such as an image contrastsetting, and can perform the above mentioned repetitive process.Finally, the camera settings can be automatically optimized so as toreproduce the original conditions (e.g., lighting condition and colorcondition) of the reference image(s), and a live image with the highestmatching percentage can be obtained after adjusting different types ofsettings of the camera 202, in one embodiment.

The comparator 206 can generate a final recognition result based on thehighest matching percentage after adjusting one or more camera settings.In one embodiment, if the highest matching percentage is greater than apredetermined threshold, which can indicate that the live image issuccessfully matched to a reference image of a person or to a group ofreference images of a person, then the facial recognition system 200declares a successful recognition. If the highest matching percentage isless than the predetermined threshold, which can indicate that nomatched reference image is found in the reference image database 204,then the facial recognition system 200 declares a recognition failure.The predetermined threshold can be set/programmed by auser/administrator of the facial recognition system 200.

Advantageously, in one embodiment, the camera settings can beautomatically optimized by a feedback signal generated by the comparator206 based on the live image and the reference image(s). With theoptimized settings, the facial recognition system 200 can reproduce theoriginal conditions (e.g., lighting and/or color conditions) of thereference image(s), and optimize the recognition probability, which canhelp improve the recognition process.

FIG. 3 illustrates a computer system 300 according to one embodiment ofpresent invention. FIG. 3 shows an implementation of the facialrecognition system 200 in FIG. 2 on a computer system 300. Elementslabeled the same as in FIG. 2 have similar functions and will not berepetitively described herein for purposes of brevity and clarity.

The computer system 300 includes an image capturing device, such as acamera 202, for capturing a live image. A storage system 304 is capableof storing a sequence of machine-readable instructions 308. The storagesystem 304 can also store a reference image database 204 including oneor more reference images. The storage system 304 can be volatile memorysuch as static random access memory (SRAM), non-volatile memory such ashard disk drive, or any combination thereof. A processor 302 is coupledto the storage system 304 for executing the sequence of machine-readableinstructions 308 to perform the functionalities of the comparator 206showing in FIG. 2, e.g., to generate a feedback signal which can adjustat lease one setting of the camera 202 by comparing the first live imagewith the reference image(s). The camera 202 is coupled to the processor302 via a camera driver 306. The camera driver 306 includes a datainterface 310 that can be various kinds of interfaces, including but isnot limited to, standard Windows USB video device class interface and analternate device software programming interface. Through the datainterface 310 in the camera driver 306, the processor 302 is capable ofadjusting at lease one setting of the camera 202 by the feedback signal.The processor 302 can be further capable of acquiring information aboutcurrent camera settings through the data interface 310.

In operation, the camera 202 captures a live image. The processor 302executes the sequence of machine-readable instructions 308 to comparethe live image with the reference image(s) from the reference imagedatabase 204. The processor 302 can generate a feedback signal bycomparing the live image with the reference image(s). In one embodiment,the feedback signal can include some commands that can adjust the camerasettings through the data interface 310 in the camera driver 306. As aresult, the camera settings can be adjusted according to the feedbacksignal through the data interface 310 in the camera driver 306, based onthe live image and the reference image(s).

FIG. 4 illustrates a flowchart 400 of optimizing camera settings, inaccordance with one embodiment of the present invention. FIG. 4 isdescribed in combination with FIG. 2. Although specific steps aredisclosed in FIG. 4, such steps are exemplary. That is, the presentinvention is well suited to performing various other steps or variationsof the steps recited in FIG. 4.

In block 402, one or more reference images are stored in a referenceimage database 204. In block 404, the camera 202 captures a live imageof a current user. In block 406, the live image is compared with areference image or with a group of reference images in the referenceimage database 204, by the comparator 206. In block 407, a currentmatching percentage is determined by the comparator 206 based on thelive image and the reference image(s). In block 411, if a previousmatching percentage is available, a direction of adjustment isdetermined by the comparator 206 based on the current and previousmatching percentage. If the current matching percentage is greater thanthe previous matching percentage, a forward direction of adjustment isdetermined, in one embodiment. If the current matching percentage isless than the previous matching percentage, a backward direction ofadjustment is determined, in one embodiment. In block 412, a feedbacksignal is generated by the comparator 206 based on the live image andthe reference image(s) and based on the direction of adjustment. Inblock 416, at least one setting of the camera 202 is adjusted by thefeedback signal. In one embodiment, an image brightness setting isadjusted. In one embodiment, an image contrast setting is adjusted. Thenthe flowchart 400 goes back to block 404 to capture a second live image,after at least one setting of the camera 202 is adjusted. Steps followedby block 404 have been described and will not be repetitively describedherein for purposes of brevity and clarity.

This method of optimizing the settings of the camera in the presentdisclosure is not limited in facial recognition system. It can also beused in other webcam applications, such as video conference systems andonline instant messengers, to optimize settings of the camera based on afeedback according to a comparison between a current live image and thepre-stored reference image(s). Therefore, the performance of such webcamapplications can be improved.

The terms and expressions which have been employed herein are used asterms of description and not of limitation, and there is no intention,in the use of such terms and expressions, of excluding any equivalentsof the features shown and described (or portions thereof), and it isrecognized that various modifications are possible within the scope ofthe claims. Other modifications, variations, and alternatives are alsopossible. Accordingly, the claims are intended to cover all suchequivalents.

1. An electronic system comprising: an image capturing device forcapturing a first live image; and a comparator coupled to said imagecapturing device for generating a feedback signal by comparing saidfirst live image with a reference image and for adjusting at least onesetting of said image capturing device by said feedback signal.
 2. Theelectronic system of claim 1, wherein said at least one setting of saidimage capturing device comprises an image brightness setting.
 3. Theelectronic system of claim 1, wherein said at least one setting of saidimage capturing device comprises an image contrast setting.
 4. Theelectronic system of claim 1, wherein said comparator determines a firstmatching percentage by comparing said first live image with saidreference image.
 5. The electronic system of claim 4, wherein said imagecapturing device captures a second live image after said at least onesetting of said image capturing device is adjusted, and wherein saidcomparator determines a second matching percentage by comparing saidsecond live image with said reference image.
 6. The electronic system ofclaim 5, wherein said comparator determines a direction of adjustment ofsaid at least one setting of said image capturing device based on saidfirst matching percentage and second matching percentage.
 7. Theelectronic system of claim 1, wherein said electronic system comprises afacial recognition system.
 8. The electronic system of claim 1, whereinsaid electronic system comprises a video conference system.
 9. Acomputer system, comprising: an image capturing device for capturing afirst live image; and a storage system coupled to said image capturingdevice for storing a sequence of machine-readable instructions; and aprocessor coupled to said storage system for executing said sequence ofmachine-readable instructions and for generating a feedback signal bycomparing said first live image with a reference image, and foradjusting at least one setting of said image capturing device by saidfeedback signal.
 10. The computer system of claim 9, wherein said atleast one setting of said image capturing device comprises an imagebrightness setting.
 11. The computer system of claim 9, wherein said atleast one setting of said image capturing device comprises an imagecontrast setting.
 12. The computer system of claim 9, wherein saidprocessor determines a first matching percentage by comparing said firstlive image with said reference image.
 13. The computer system of claim12, wherein said image capturing device captures a second live imageafter said at least one setting of said image capturing device isadjusted, and wherein said processor determines a second matchingpercentage by comparing said second live image with said referenceimage.
 14. The computer system of claim 13, wherein said processordetermines a direction of adjustment of said at least one setting ofsaid image capturing device based on said first matching percentage andsecond matching percentage.
 15. A method for optimizing at least onesetting of an image capturing device, comprising: capturing a first liveimage by said image capturing device; generating a feedback signal bycomparing said first live image with a reference image; and adjustingsaid at least one setting of said image capturing device according tosaid feedback signal.
 16. The method of claim 15, wherein adjusting saidat least one setting of said image capturing device with said feedbacksignal comprises: adjusting an image brightness setting of said imagecapturing device.
 17. The method of claim 15, wherein adjusting said atleast one setting of said image capturing device with said feedbacksignal comprises: adjusting an image contrast setting of said imagecapturing device.
 18. The method of claim 15, further comprising:determining a first matching percentage by comparing said first liveimage with said reference image.
 19. The method of claim 18, furthercomprising: capturing a second live image after said at least onesetting of said image capturing device is adjusted; and determining asecond matching percentage by comparing said second live image with saidreference image.
 20. The method of claim 19, further comprising:determining a direction of adjustment of said at least one setting ofsaid image capturing device based on said first matching percentage andsecond matching percentage.